Introductory Biostatistics

(a) Aframefor a 2 2 tablewith places identified asrow, column, and

data

(b) Names of the factors you chose: say,exposure, disease, andfake

Step 2: Dragexposure to merge with row (or column),dragdisease to

merge with column (or row), anddragfake to merge with data. Then

clickFinish;a2 2 tableappears in the active cell you identified, com-

plete withcell frequencies, row and column totals, andgrand total.

Note:If you have anotherfactorin addition to exposure and disease avail-
able in the data set, even a column fornamesorIDs, there is no need to create
thedummy factor. Complete step 1; then, in step 2,drag that third factor, say
ID, to merge with ‘‘data’’ in the frame shown by thePivotTable Wizard;it
appears assum ID. Click on that item, then choosecount(to replacesum).

EXERCISES

1.1 Self-reported injuries among left- and right-handed people were com-

pared in a survey of 1896 college students in British Columbia, Canada.

Of the 180 left-handed students, 93 reported at least one injury, and 619

of the 1716 right-handed students reported at least one injury in the same

period. Arrange the data in a 22 table and calculate the proportion of

people with at least one injury during the period of observation for each

group.

1.2 A study was conducted to evaluate the hypothesis that tea consumption

and premenstrual syndrome are associated. A group of 188 nursing stu-

dents and 64 tea factory workers were given questionnaires. The preva-

lence of premenstrual syndrome was 39% among the nursing students

and 77% among the tea factory workers. How many people in each

group have premenstrual syndrome? Arrange the data in a 22 table.

1.3 The relationship between prior condom use and tubal pregnancy was

assessed in a population-based case–control study at Group Health

Cooperative of Puget Sound during 1981–1986. The results are shown in

Table E1.3. Compute the group size and the proportion of subjects in

each group who never used condoms.

TABLE E1.3

Condom Use Cases Controls

Never 176 488

Ever 51 186

34 DESCRIPTIVE METHODS FOR CATEGORICAL DATA